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cs.CV2026

GenVideoLens: Where LVLMs Fall Short in AI-Generated Video Detection?

Yueying Zou, Pei Pei Li, Zekun Li +4

In recent years, AI-generated videos have become increasingly realistic and sophisticated. Meanwhile, Large Vision-Language Models (LVLMs) have shown strong potential for detecting…

cs.CV2025

Video-SafetyBench: A Benchmark for Safety Evaluation of Video LVLMs

Xuannan Liu, Zekun Li, Zheqi He +6

The increasing deployment of Large Vision-Language Models (LVLMs) raises safety concerns under potential malicious inputs. However, existing multimodal safety evaluations primarily…

cs.CV2025

ID-Cloak: Crafting Identity-Specific Cloaks Against Personalized Text-to-Image Generation

Qianrui Teng, Xing Cui, Xuannan Liu +4

Personalized text-to-image models allow users to generate images of new concepts from several reference photos, thereby leading to critical concerns regarding civil privacy. Althou…

cs.CV2025

Survey on AI-Generated Media Detection: From Non-MLLM to MLLM

Yueying Zou, Peipei Li, Zekun Li +5

The proliferation of AI-generated media poses significant challenges to information authenticity and social trust, making reliable detection methods highly demanded. Methods for de…

cs.CV2024

Jailbreak Attacks and Defenses against Multimodal Generative Models: A Survey

Xuannan Liu, Xing Cui, Peipei Li +6

The rapid evolution of multimodal foundation models has led to significant advancements in cross-modal understanding and generation across diverse modalities, including text, image…